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Publication Date
2023-5
First Advisor
Arantxa Cuadra
Second Advisor
Michael Kinsinger
Document Type
Honors Project
Degree Name
Bachelor of Arts
Department
Engineering
Keywords
nuclear data, nuclear engineering, nuclear reactor, MCNP, uncertainty quantification, computer modeling, Brookhaven National Laboratory, National Nuclear Data Center, NBSR, NIST, research reactor
Abstract
In recent decades, the US Nuclear Regulatory Commission (NRC) has been transitioning from a conservative method of reactor safety analysis to a “Best Estimate Plus Uncertainty” (BEPU) method. This switch allows for greater levels of optimization in reactor systems by using more accurate model inputs but also requires sufficient tools to perform the uncertainty analysis. One contributor of uncertainty that is of great interest to the National Nuclear Data Center (NNDC) at Brookhaven National Laboratory is how the uncertainty on nuclear data, characterized by covariances, propagates through and biases model results. The neutronics code MCNP (Monte Carlo N-Particle transport code) developed by Los Alamos National Laboratory is the gold-standard code for modeling the transport of neutrons in reactors and is used to calculate the effective neutron multiplication factor, keff. However, MCNP cannot perform uncertainty quantification (UQ) for nuclear data inputs. Other neutron transport code packages, such as SCALE and Serpent, have implemented the sandwich formula to accomplish this task. Therefore, the goal of this work was to build an external sandwich formula widget to pair with MCNP. The sandwich formula is a UQ method that calculates the uncertainty on keff by multiplying nuclear data covariances with the neutron-transport code’s sensitivity coefficients. The software package includes a script which can manage the running of NJOY2016 to produce covariance matrices from ENDF/B-VIII.0 and ENDF/B-VII.1 nuclear data files. The widget can process NJOY output files and MCNP keff sensitivity (KSEN) cards to calculate uncertainty with the sandwich formula. The widget was validated by using the TSUNAMI code within the SCALE package and was found to produce results within the same orders of magnitude as expected in all cases. A test case is detailed here, in which the sandwich formula widget is used on an NBSR single-assembly fuel element model and was found to have a total uncertainty of 1.09% Δk/k on a keff value of 1.40276, with fresh fuel. This tool is intended to illuminate both how nuclear data covariances as a whole propagate to uncertainty on keff and to quantify the extent to which individual isotopes bias MCNP calculations. It is expected that this software package will further the work of reactor physicists and nuclear data evaluators by providing uncertainty data that informs the design of new reactor fuel and simultaneously provides feedback to data evaluators about the effect of their evaluations on fuel models.
Rights
©2023 Name. Access limited to the Smith College community and other researchers while on campus. Smith College community members also may access from off-campus using a Smith College log-in. Other off-campus researchers may request a copy through Interlibrary Loan for personal use.
Language
English
Recommended Citation
Sears, Caroline, "Development of a Sandwich Formula Implementation Code for MCNP" (2023). Honors Project, Smith College, Northampton, MA.
https://scholarworks.smith.edu/theses/2570
Comments
xi, 150 pages : color illustrations, charts. Includes bibliographical references (pages 75-77).